Given continuous increases in the costs of healthcare systems, automated clinical decision support is likely to become a crucial feature of any modern healthcare solution. However, in order for such automated support system to exist, one may require a corpus of tests. The corpus may be used for testing the suggestions or decisions proposed by the automated system. Additionally or alternatively, the corpus may be used for training the system, in accordance with machine learning techniques.
Today, the corpus of tests may be manually designed by highly trained individuals. In order to devise a meaningful corpus, experts may invest large amounts of time to manually define the tests and indicate the correct answer for each test. Such a substantial investment may require large amounts of resources in order to develop such a system.
It will be noted, however, that though particularly relevant to clinical decision support system, the same challenge may also apply for the other automated systems, such as non-clinical decision support systems, machine learning systems, or the like.